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neuron-tai/.scratch/distributed-inference-performance/issues/06-activation-framing-copies.md
2026-07-10 01:30:07 +03:00

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Status: ready-for-agent
# 06 — Activation framing and copy reduction
## What to build
Profile and reduce avoidable allocations while activation data crosses a seam:
binary frame assembly, header JSON, base64 metadata, CPU/GPU conversion, and
response decompression. Preserve the current binary wire contract and use
zero-copy or pooled buffers only where ownership and lifetime are explicit.
## Acceptance criteria
- [ ] The benchmark identifies copy/allocation cost separately from model and
network time.
- [ ] Decode hidden-state conversion has no unnecessary float32 round trip.
- [ ] Binary framing avoids base64 for activation bodies and does not retain
buffers after a request completes.
- [ ] Position/attention metadata is validated and encoded efficiently without
changing semantic headers or cache positions.
- [ ] A focused test proves byte-for-byte wire compatibility and stable output
tokens before and after the optimization.
## Blocked by
- 01 — Baseline and profiling harness.